• DocumentCode
    4512
  • Title

    Cross-Layer Design of Distributed Sensing-Estimation With Quality Feedback— Part II: Myopic Schemes

  • Author

    Michelusi, Nicolo ; Mitra, Urbashi

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
  • Volume
    63
  • Issue
    5
  • fYear
    2015
  • fDate
    1-Mar-15
  • Firstpage
    1244
  • Lastpage
    1258
  • Abstract
    This two-part paper presents a feedback-based cross-layer framework for distributed sensing and estimation of a dynamic process by a wireless sensor network (WSN). Sensor nodes wirelessly communicate measurements to the fusion center (FC). Cross-layer factors such as packet collisions and the sensing-transmission costs are considered. Each SN adapts its sensing-transmission action based on its own local observation quality and the estimation quality feedback from the FC under cost constraints for each SN. In this second part, low-complexity myopic sensing-transmission policies (MPs) are designed to optimize a trade-off between performance and the cost incurred by each SN. The MP is computed in closed form for a coordinated scheme, whereas an iterative algorithm is presented for a decentralized one, which converges to a local optimum. The MP dictates that, when the estimation quality is poor, only the best SNs activate, otherwise all SNs remain idle to preserve energy. For both schemes, the threshold on the estimation quality below which the SNs remain idle is derived in closed form, and is shown to be independent of the number of channels. It is also proved that a single channel suffices for severely energy constrained WSNs. The proposed MPs are shown to yield near-optimal performance with respect to the optimal policy of Part I, also in this issue, at a fraction of the complexity, thus being more suitable for practical WSN deployments.
  • Keywords
    iterative methods; wireless sensor networks; WSN; cross-layer factors; distributed sensing-estimation cross-layer design; estimation quality; fusion center; iterative algorithm; myopic sensing-transmission policies; packet collisions; sensing-transmission costs; sensor nodes; wireless sensor network; Complexity theory; Estimation; Kalman filters; Sensors; Signal to noise ratio; Tin; Wireless sensor networks; Distributed estimation; Markov decision processes; cross-layer optimization; wireless networks;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2014.2388440
  • Filename
    7001684